Project Summary There is considerable interest in developing new quantitative imaging methods to monitor and predict breast cancer response to neoadjuvant chemotherapy (NAC), both prior to and as early as possible during the course of treatment. Diffuse optical spectroscopic imaging (DOSI) allows patients to be followed from baseline through treatment and surgery with a cost-effective, bedside, handheld scanning probe. In this competing renewal application, we propose to further advance the development of a standardized DOSI technology platform by introducing a new, portable, miniature device (m-DOSI) that has significantly reduced cost and size with equivalent performance compared to existing instruments. m-DOSI scanners will be constructed and delivered to all collaborating clinical sites and up to 150 pre-surgical NAC patients will be evaluated in multi- center studies. Our goal is to establish quantitative DOSI functional endpoints of NAC response that predict patient clinical outcome as measured by pathologic complete response (pCR). In order to optimize the power of DOSI predictions and ease of integration into the clinical work flow, we propose to validate three measurement time-points and DOSI endpoints first discovered in our current funding cycle: 1) Tissue oxygen saturation prior to chemotherapy infusion, 2) Tissue oxyhemoglobin concentration one day following the first infusion, and 3) a Tissue optical index (TOI) at the midpoint of NAC prior to switching drug regimens. Tumor hemodynamics will also be investigated during the first week of therapy. NAC midpoint response is currently undergoing evaluation as part of our American College of Radiology Imaging Network 60-patient multi-center clinical trial (ACRIN-6691) that completed enrollment in March 2013, two months prior to the originally anticipated June 2013 end date. We hypothesize that the combination of pre-therapy and one-day post- infusion measurements with the ACRIN mid-point assessment will provide a more practical and improved approach for managing patients. In order to develop new insight into achieving pCR in the challenging triple negative (TN) breast cancer population we will stratify response by molecular subtype and adjust our multi- endpoint predictive model for the TN subgroup. Finally, we will continue to optimize and improve m-DOSI functionality, standardize clinical measurement and analysis procedures, and evaluate whether m-DOSI can be used with equivalent overall performance by different operators. Our long-term goal is to identify the right combination of quantitative clinical endpoints for informing medical decisions on chemotherapy regimen, duration, and timing of surgery. Ultimately this work is expected to lead to a bedside optical imaging technology that can be used to improve patient outcome by maximizing therapeutic response, minimizing unnecessary toxicity, and optimizing clinical decision-making.